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Unity Catalog: Databricks *Specific* Features

ChristianRRL
Contributor II

Good day,

Deceptively simple question, are there any "Databricks only" specific features that Unity Catalog offers? I understand that generally speaking enabling UC offers some of the following:

  • Data Discovery and Lineage
  • Auditing and Monitoring
  • Access Control
  • Data Sharing

However, I'm wondering if there are specific features (either related to the above or not) UC provides that are either "technically impossible" or "unreasonably difficult" to implement with 3rd party tools?

1 ACCEPTED SOLUTION

Accepted Solutions

Kaniz_Fatma
Community Manager
Community Manager

Hi @ChristianRRL,  Unity Catalog is a powerful governance solution for data and AI assets within the Databricks lakehouse

 

Let’s delve into its key features and explore how it differs from other tools:

 

Define Once, Secure Everywhere:

  • Unity Catalog allows you to administer data access policies centrally across all workspaces within Databricks.
  • This feature simplifies security management by ensuring consistent access controls regardless of the workspace.

Standards-Compliant Security Model:

  • Unity Catalog’s security model adheres to ANSI SQL standards.
  • Administrators can grant permissions using familiar syntax at different levels:
    • Catalogs: Logical groupings of schemas (bounded by data access requirements).
    • Databases (Schemas): Organizational or lifecycle scopes.
    • Tables and Views: Granular access control.
  • This standardization makes it easier to manage permissions across your data lake.

Built-In Auditing and Lineage:

  • Unity Catalog automatically captures user-level audit logs for data access.
  • It also tracks lineage data, showing how data assets are created and used across all languages.
  • This lineage information is invaluable for understanding data flow and dependencies.

Data Discovery:

  • You can tag and document data assets within Unity Catalog.
  • The search interface helps data consumers quickly find relevant data.
  • This feature enhances data discoverability and promotes efficient data exploration.

System Tables (Public Preview):

  • Unity Catalog provides access to operational data, including:
    • Audit logs: Record of data access.
    • Billable usage: Insights into resource consumption.
    • Lineage information: Understanding data flow.
  • These system tables facilitate monitoring and governance.

Now, let’s address your specific question about features that might be “technically impossible” or “unreasonably difficult” to implement with 3rd party tools:

 

Managed Storage Locations:

  • Unity Catalog associates storage locations in Azure Data Lake Storage Gen2 containers with catalogs, schemas, or metastores.
  • These managed storage locations serve as default storage for managed tables and volumes.
  • Achieving this level of integration with external tools could be challenging.

Lakehouse Federation:

  • Unity Catalog integrates seamlessly with the concept of a lakehouse, combining data lakes and data warehouses.
  • While some features may be emulated by 3rd party tools, the tight integration with Databricks’ lakehouse architecture is unique.

In summary, Unity Catalog’s combination of centralized governance, lineage tracking, and seamless integration with Databricks makes it a powerful choice for managing data and AI assets. While some aspects may be replicated by other tools, the depth of integration and ease of administration set Unity Catalog apart. 🚀🔍

 

For more details, you can refer to the official documentation.

View solution in original post

1 REPLY 1

Kaniz_Fatma
Community Manager
Community Manager

Hi @ChristianRRL,  Unity Catalog is a powerful governance solution for data and AI assets within the Databricks lakehouse

 

Let’s delve into its key features and explore how it differs from other tools:

 

Define Once, Secure Everywhere:

  • Unity Catalog allows you to administer data access policies centrally across all workspaces within Databricks.
  • This feature simplifies security management by ensuring consistent access controls regardless of the workspace.

Standards-Compliant Security Model:

  • Unity Catalog’s security model adheres to ANSI SQL standards.
  • Administrators can grant permissions using familiar syntax at different levels:
    • Catalogs: Logical groupings of schemas (bounded by data access requirements).
    • Databases (Schemas): Organizational or lifecycle scopes.
    • Tables and Views: Granular access control.
  • This standardization makes it easier to manage permissions across your data lake.

Built-In Auditing and Lineage:

  • Unity Catalog automatically captures user-level audit logs for data access.
  • It also tracks lineage data, showing how data assets are created and used across all languages.
  • This lineage information is invaluable for understanding data flow and dependencies.

Data Discovery:

  • You can tag and document data assets within Unity Catalog.
  • The search interface helps data consumers quickly find relevant data.
  • This feature enhances data discoverability and promotes efficient data exploration.

System Tables (Public Preview):

  • Unity Catalog provides access to operational data, including:
    • Audit logs: Record of data access.
    • Billable usage: Insights into resource consumption.
    • Lineage information: Understanding data flow.
  • These system tables facilitate monitoring and governance.

Now, let’s address your specific question about features that might be “technically impossible” or “unreasonably difficult” to implement with 3rd party tools:

 

Managed Storage Locations:

  • Unity Catalog associates storage locations in Azure Data Lake Storage Gen2 containers with catalogs, schemas, or metastores.
  • These managed storage locations serve as default storage for managed tables and volumes.
  • Achieving this level of integration with external tools could be challenging.

Lakehouse Federation:

  • Unity Catalog integrates seamlessly with the concept of a lakehouse, combining data lakes and data warehouses.
  • While some features may be emulated by 3rd party tools, the tight integration with Databricks’ lakehouse architecture is unique.

In summary, Unity Catalog’s combination of centralized governance, lineage tracking, and seamless integration with Databricks makes it a powerful choice for managing data and AI assets. While some aspects may be replicated by other tools, the depth of integration and ease of administration set Unity Catalog apart. 🚀🔍

 

For more details, you can refer to the official documentation.

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